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市场调查报告书
商品编码
1871971
智慧型穿戴脑电图设备:全球市场份额和排名、总收入和需求预测(2025-2031年)Smart Wearable EEG Device - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031 |
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2024 年全球智慧型穿戴脑电图设备市场规模估计为 1.58 亿美元,预计到 2031 年将达到 5.82 亿美元,在预测期(2025-2031 年)内复合年增长率为 19.8%。
本报告对近期有关智慧型穿戴脑电图设备的关税调整和国际策略反制措施进行了全面评估,包括跨境产业布局、资本配置模式、区域经济相互依存关係和供应链重组。
智慧型穿戴脑电图(EEG)设备是消费级穿戴设备,用于测量脑电波。它们使用放置在前额的脑电图感测器来检测大脑活动并记录电活动。然后,该可穿戴设备与程式和应用程式配合使用,将数据转化为对用户有用的信息。
全球主要的智慧可穿戴脑电图(EEG)设备製造商包括InteraXon、Neurosky、Macrotellect和Emotiv。前四大公司占了约80%的市场。亚太地区是智慧穿戴式脑电图设备最大的市场,市占率超过45%。按产品类型划分,头戴式设备占据最大市场份额,约占51%;预计到2028年,头带式设备将成为最大市场份额,约占51%。依应用领域划分,科学研究和教育是最大的应用领域,约占55%。
智慧型穿戴脑电图设备的主要市场驱动因素包括:
科技进步:核心驱动力
先进的传感器和演算法
柔性电子技术:微型无线感测器(例如REMI)克服了传统设备体积庞大的局限性,可实现居家长期监测。 REMI感测器在时域和频域均检验出较高的相关性(0.86-0.94),其癫痫发作检测性能与有线设备相当。 69%的使用者认为配戴舒适。
人工智慧演算法创新:深度学习模型(CNN、LSTM、 变压器)在脑电讯号处理方面表现优异。例如:
【癫痫检测】CNN-LSTM 组合模型在公开资料集上实现了三分类 98% 的准确率和二分类 100% 的准确率。
情绪辨识:基于 CNN-RNN 的模型能够从脑电讯号中实现多情绪分类,并应用于心理健康监测和互动式系统。
资料处理能力提升
即时监测和预警:人工智慧演算法实现对脑电讯号的即时分析,并在诊断睡眠障碍和帕金森氏症方面提供即时回馈。
个人化医疗:透过将使用者的基因资讯与临床症状结合,人工智慧将客製化治疗方案,促进精准医疗的发展。
消费者需求:日益增强的健康意识
医疗保健需求飙升
疲劳和睡眠问题:在中国青少年和高压力人群中,分别有 59.1% 和 57.1% 的人患有疲劳问题,而高压力人群中有 42.9% 的人患有记忆问题,这推动了对睡眠监测设备的需求。
心理健康问题:过度压力已成为中青年族群面临的主要心理问题。脑电图设备可透过情绪辨识技术(例如,DEAP资料集)提供心理健康监测和介入。
扩展应用场景
医疗诊断:对癫痫、睡眠障碍等疾病进行家庭监测和早期诊断。
非医疗领域:
教育:注意力训练(例如,脑机介面以提高学习能力)。
游戏互动:脑电图控制设备(例如,SSVEP、P300 讯号驱动的虚拟角色操作)。
电竞优化:FocusBand 使用脑电图 (EEG) 来优化玩家的专注力并提高竞技表现。
政策支持:促进高层设计
国家战略方向
「健康中国2030」计画概述:将健康定位为优先发展策略,并推广穿戴式装置在疾病预防和健康管理的应用。
智慧医疗产业发展行动计画(2021-2025):明确老年照护场所智慧型装置的标准及其针对老年人的设计,促进科技的广泛应用。
行业标准和规范
医疗设备监管:国家食品药物管理局将推进医疗领域穿戴式装置的合格评定,以确保讯号品质和临床疗效。
消费促进政策:2023年国务院《恢復与扩大消费措施》将明确规定支持穿戴式装置消费,并为电子产品创造新的应用情境。
技术整合与创新
深化脑机介面:将脑电图 (EEG) 与扩增实境/虚拟实境 (AR/VR) 结合,创造更自然的互动体验。
多模态数据整合:整合心率和皮肤电讯号等多维数据,以提高诊断准确性。
市场挑战
资料隐私与安全:脑电图资料包含敏感的健康讯息,需要加密和加强合规控制。
需要临床检验:某些设备在复杂病例中的准确性仍需进行广泛的临床检验。
政策改善方向
健康保险覆盖范围:促进将穿戴式脑电图设备纳入健康保险覆盖范围,减少使用者采用的障碍。
国际标准的协调统一:全球技术标准和认证流程的协调统一将促进跨境市场扩张。
智慧型穿戴脑电图(EEG)设备的市场成长受到技术创新、健康意识提升、政策利好、製造商创新以及消费者认知水平提高的驱动。随着人工智慧演算法的最佳化、感测器效能的提升以及政策的完善,这些设备将进一步融入医疗、教育、娱乐等多种场景,从而形成以使用者为中心的健康管理生态系统。
本报告旨在按地区/国家、类型和应用对全球智慧穿戴脑电图设备市场进行全面分析,重点关注总销售量、收入、价格、市场份额和主要企业的排名。
本报告以销售量和收入(百万美元)为单位,对智慧穿戴式脑电图(EEG)设备的市场规模、估值和预测进行了呈现,以2024年为基准年,并涵盖了2020年至2031年的历史数据和预测数据。定量和定性分析将帮助读者制定业务和成长策略,评估市场竞争,分析自身在当前市场中的地位,并就智慧穿戴脑电图设备做出明智的商业决策。
市场区隔
公司
按类型分類的细分市场
应用领域
按地区
The global market for Smart Wearable EEG Device was estimated to be worth US$ 158 million in 2024 and is forecast to a readjusted size of US$ 582 million by 2031 with a CAGR of 19.8% during the forecast period 2025-2031.
This report provides a comprehensive assessment of recent tariff adjustments and international strategic countermeasures on Smart Wearable EEG Device cross-border industrial footprints, capital allocation patterns, regional economic interdependencies, and supply chain reconfigurations.
A Smart Wearable EEG Device is a consumer-grade wearable device for electroencephalography. The device records the electrical activity of the brain by using EEG sensors placed along the forehead to detect brain activity. The wearable device then communicates with a program or app to interpret the data into valuable information for the user.
Global key manufacturers of Smart Wearable EEG Device include InteraXon, Neurosky, Macrotellect, Emotiv, etc. Global top four manufacturers hold a share about 80%. Asia-Pacific is the largest market of Smart Wearable EEG Device, holds a share over 45%. In terms of product, the headset holds a larger segment, with a share about 51%, but it is predicted that by 2028, the headband would holds a larger segment of about 51%. And in terms of application, the largest application is research and education, with a share of about 55%.
The main market drivers of smart wearable EEG devices include the following:
Technological progress: the core driving force
Sensor and algorithm upgrade
Flexible electronic technology: micro wireless sensors (such as REMI) break through the bulky limitations of traditional devices and achieve long-term monitoring at home. REMI sensors have been verified by high correlation in the time domain/frequency domain (0.86-0.94), and their performance is comparable to that of wired devices in epileptic seizure detection, and 69% of users recognize their comfort.
AI algorithm breakthrough: Deep learning models (CNN, LSTM, Transformer) perform well in EEG signal processing. For example:
Epilepsy detection: The CNN-LSTM combination model achieves 98% ternary classification accuracy and 100% binary classification accuracy on public data sets.
Emotion recognition: The CNN-RNN-based model realizes multi-emotion classification through EEG signals and is applied to mental health monitoring and interactive systems.
Data processing capability improvement
Real-time monitoring and early warning: AI algorithms realize real-time analysis of EEG signals, such as providing instant feedback in the diagnosis of sleep disorders and Parkinson's disease.
Personalized medicine: Combining user genetic information with clinical symptoms, AI customizes treatment plans to promote the development of precision medicine.
Consumer demand: Awakening of health awareness
Demand for health management surges
Fatigue and sleep problems: Among Chinese teenagers and high-pressure people, 59.1% and 57.1% have fatigue problems, and 42.9% of high-pressure people suffer from memory loss, which drives the demand for sleep monitoring equipment.
Mental health concerns: Excessive stress has become a major psychological problem for young and middle-aged people. EEG equipment provides mental health monitoring and intervention through emotion recognition technology (such as DEAP dataset).
Application scenario expansion
Medical diagnosis: Home monitoring and early diagnosis of diseases such as epilepsy and sleep disorders.
Non-medical scenarios:
Education: Attention training (such as brain-computer interface to improve learning efficiency).
Games and interactions: Brain control equipment (such as SSVEP, P300 signal-driven virtual character control).
E-sports optimization: FocusBand optimizes players' concentration through EEG to improve competitive performance.
Policy support: top-level design promotion
National strategic orientation
Outline of the "Healthy China 2030" Plan: Put health in the priority development strategy and promote the application of wearable devices in disease prevention and health management.
Action Plan for the Development of Smart Health Care Industry (2021-2025): Clarify the standard construction and aging-friendly design of smart devices in the elderly care scene and promote the popularization of technology.
Industry standards and specifications
Medical device supervision: The State Food and Drug Administration promotes compliance certification of wearable devices in the medical field to ensure signal quality and clinical effectiveness.
Consumption encouragement policy: The State Council's "Measures on Restoring and Expanding Consumption" in 2023 clearly supports the consumption of wearable devices and creates new scenarios for the application of electronic products.
Technology integration and innovation
Deepening of brain-computer interface: EEG is combined with AR/VR to achieve a more natural interactive experience.
Multimodal data integration: Integrate multi-dimensional data such as heart rate and skin electrical signals to improve diagnostic accuracy.
Market challenges
Data privacy and security: EEG data involves sensitive health information, and encryption and compliance management need to be strengthened.
Clinical verification needs: The accuracy of some devices in complex cases still needs large-scale clinical verification.
Policy refinement direction
Medical insurance coverage: Promote the inclusion of wearable EEG devices in the scope of medical insurance reimbursement to lower the threshold for users to use.
International standard unification: Coordinate global technical standards and certification processes to promote cross-border market expansion.
The market growth of smart wearable EEG devices is driven by technological innovation, health awareness, policy dividends, manufacturer innovation and consumption upgrades. In the future, with the optimization of AI algorithms, the improvement of sensor performance and the refinement of policies, the equipment will further penetrate multiple scenarios such as medical care, education, and entertainment, forming a user-centered health management ecosystem.
This report aims to provide a comprehensive presentation of the global market for Smart Wearable EEG Device, focusing on the total sales volume, sales revenue, price, key companies market share and ranking, together with an analysis of Smart Wearable EEG Device by region & country, by Type, and by Application.
The Smart Wearable EEG Device market size, estimations, and forecasts are provided in terms of sales volume (Units) and sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Smart Wearable EEG Device.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size (value, volume and price). This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Smart Wearable EEG Device manufacturers competitive landscape, price, sales and revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Sales, revenue of Smart Wearable EEG Device in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Sales, revenue of Smart Wearable EEG Device in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.